{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CHAPTER 5 First-class functions\n",
    "Functions in Python are first-class objects. Programming language theorists define a\n",
    "“first-class object” as a program entity that can be:\n",
    "• created at runtime;\n",
    "• assigned to a variable or element in a data structure;\n",
    "• passed as an argument to a function;\n",
    "• returned as the result of a function.\n",
    "## Treating a function like an object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def factorial(n):\n",
    "     '''returns n!'''\n",
    "     return 1 if n < 2 else n * factorial(n-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1405006117752879898543142606244511569936384000000000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factorial(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'returns n!'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factorial.__doc__\n",
    "#The __doc__ attribute is used to generate the help text of an object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "function"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(factorial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function factorial in module __main__:\n",
      "\n",
      "factorial(n)\n",
      "    returns n!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(factorial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function __main__.factorial>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fact=factorial\n",
    "fact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "120"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fact(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<map at 0x5a08390>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "map(factorial, range(11))\n",
    "#map(function, iterable, ...)\n",
    "#Return an iterator that applies function to every item of iterable, yielding the results. \n",
    "#If additional iterable arguments are passed, function must take that many arguments and is \n",
    "#applied to the items from all iterables in parallel. With multiple iterables, the iterator\n",
    "#stops when the shortest iterable is exhausted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880, 3628800]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(fact, range(11)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Higher-order functions\n",
    "A function that takes a function as argument or returns a function as result is a higherorder\n",
    "function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['fig', 'apple', 'cherry', 'banana', 'raspberry', 'strawberry']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits = ['strawberry', 'fig', 'apple', 'cherry', 'raspberry', 'banana']\n",
    "sorted(fruits,key=len)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "def reverse(word):\n",
    "    return word[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['banana', 'apple', 'fig', 'raspberry', 'strawberry', 'cherry']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(fruits, key=reverse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modern replacements for map, filter and reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 1, 2, 6, 24, 120]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(fact, range(6)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 1, 2, 6, 24, 120]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[fact(n) for n in range(6)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 6, 120]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(factorial, filter(lambda n: n % 2, range(6))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 6, 120]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[factorial(n) for n in range(6) if n % 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4950"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from functools import reduce\n",
    "from operator import add\n",
    "reduce(add, range(100))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4950"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(range(100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other reducing built-ins are all and any:\n",
    "all(iterable)\n",
    "return True if every element of the iterable is truthy; all([]) returns True.\n",
    "any(iterable)\n",
    "return True if any element of the iterable is truthy; all([]) returns False.\n",
    "##  Anonymous functions\n",
    "The lambda keyword creates an anonymous function within a Python expression."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['banana', 'apple', 'fig', 'raspberry', 'strawberry', 'cherry']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fruits = ['strawberry', 'fig', 'apple', 'cherry', 'raspberry', 'banana']\n",
    "sorted(fruits, key=lambda word: word[::-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The seven flavors of callable objects\n",
    "The call operator, i.e. (), may be applied to other objects beyond user-defined functions.\n",
    "To determine whether an object is callable, use the callable() built-in function. The\n",
    "Python Data Model documentation lists seven callable types:\n",
    "User-defined functions\n",
    "created with def statements or lambda expressions.\n",
    "Built-in functions\n",
    "a function implemented in C (for CPython), like len or time.strftime.\n",
    "Built-in methods\n",
    "methods implemented in C, like dict.get.\n",
    "Methods\n",
    "functions defined in the body of a class.\n",
    "Classes\n",
    "when invoked, a class runs its __new__ method to create an instance, then __in\n",
    "it__ to initialize it, and finally the instance is returned to the caller. Because there\n",
    "is no new operator in Python, calling a class is like calling a function2.\n",
    "Class instances\n",
    "if a class defines a __call__ method, then its instances may be invoked as functions.\n",
    "See “User defined callable types” on page 145 below.\n",
    "Generator functions\n",
    "functions or methods that use the yield keyword. When called, generator functions\n",
    "return a generator object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[True, True, False]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[callable(obj) for obj in (abs, str, 13)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## User defined callable types\n",
    "Not only are Python functions real objects, but arbitrary Python objects may also be\n",
    "made to behave like functions. Implementing a __call__ instance method is all it takes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import random\n",
    "class BingoCage:\n",
    "    def __init__(self, items):\n",
    "        self._items = list(items)\n",
    "        random.shuffle(self._items)\n",
    "    def pick(self):\n",
    "        try:\n",
    "            return self._items.pop()\n",
    "        except IndexError:\n",
    "            raise LookupError('pick from empty BingoCage')\n",
    "    def __call__(self):\n",
    "        return self.pick()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test=BingoCage(range(3))\n",
    "test.pick()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "callable(test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Function introspection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__annotations__',\n",
       " '__call__',\n",
       " '__class__',\n",
       " '__closure__',\n",
       " '__code__',\n",
       " '__defaults__',\n",
       " '__delattr__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__get__',\n",
       " '__getattribute__',\n",
       " '__globals__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__kwdefaults__',\n",
       " '__le__',\n",
       " '__lt__',\n",
       " '__module__',\n",
       " '__name__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__qualname__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__setattr__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__subclasshook__']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(factorial)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def upper_case_name(obj):\n",
    "    return (\"%s %s\" % (obj.first_name, obj.last_name)).upper()\n",
    "upper_case_name.short_description = 'Customer name'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__annotations__',\n",
       " '__call__',\n",
       " '__closure__',\n",
       " '__code__',\n",
       " '__defaults__',\n",
       " '__get__',\n",
       " '__globals__',\n",
       " '__kwdefaults__',\n",
       " '__name__',\n",
       " '__qualname__']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class C: pass \n",
    "#pass_stmt ::=  \"pass\"\n",
    "#pass is a null operation — when it is executed, nothing happens. It is useful as a placeholder when a statement is \n",
    "#required syntactically, but no code needs to be executed\n",
    "obj = C() \n",
    "def func(): pass \n",
    "sorted(set(dir(func)) - set(dir(obj)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## From positional to keyword-only parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def tag(name, *content, cls=None, **attrs):\n",
    "    \"\"\"Generate one or more HTML tags\"\"\"\n",
    "    if cls is not None:\n",
    "        attrs['class'] = cls\n",
    "    if attrs:\n",
    "        attr_str = ''.join(' %s=\"%s\"' % (attr, value)   for attr, value in sorted(attrs.items()))\n",
    "    else:\n",
    "        attr_str = ''\n",
    "    if content:\n",
    "        return '\\n'.join('<%s%s>%s</%s>' % (name, attr_str, c, name) for c in content)\n",
    "    else:\n",
    "        return '<%s%s />' % (name, attr_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<br />'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag('br')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<p>hello</p>'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag('p', 'hello')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<p>hello</p>\n",
      "<p>world</p>\n"
     ]
    }
   ],
   "source": [
    "print(tag('p', 'hello', 'world'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<p id=\"33\">hello</p>'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag('p', 'hello', id=33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<p class=\"sidebar\">hello</p>\n",
      "<p class=\"sidebar\">world</p>\n"
     ]
    }
   ],
   "source": [
    "print(tag('p', 'hello', 'world', cls='sidebar'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<img content=\"testing\" />'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag(content='testing', name=\"img\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<img class=\"framed\" src=\"sunset.jpg\" title=\"Sunset Boulevard\" />'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_tag = {'name': 'img', 'title': 'Sunset Boulevard', 'src': 'sunset.jpg', 'cls': 'framed'}\n",
    "tag(**my_tag)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Packages for functional programming\n",
    "### The operator module\n",
    "# CHAPTER 6 Design patterns with first-class functions\n",
    "## Case study: refactoring Strategy\n",
    "### Classic Strategy\n",
    "![image.png](attachment:image.png)\n",
    "The Strategy pattern is summarized like this in the Design Patterns book:\n",
    "Define a family of algorithms, encapsulate each one, and make them interchangeable.\n",
    "Strategy lets the algorithm vary independently from clients that use it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from abc import ABC, abstractmethod\n",
    "from collections import namedtuple\n",
    "Customer = namedtuple('Customer', 'name fidelity')\n",
    "\n",
    "class LineItem:\n",
    "    def __init__(self, product, quantity, price):\n",
    "        self.product = product\n",
    "        self.quantity = quantity\n",
    "        self.price = price\n",
    "    def total(self):\n",
    "        return self.price * self.quantity\n",
    "class Order: # the Context\n",
    "    def __init__(self, customer, cart, promotion=None):\n",
    "        self.customer = customer\n",
    "        self.cart = list(cart)\n",
    "        self.promotion = promotion\n",
    "    def total(self):\n",
    "        if not hasattr(self, '__total'):\n",
    "            self.__total = sum(item.total() for item in self.cart)\n",
    "        return self.__total\n",
    "    def due(self):\n",
    "        if self.promotion is None:\n",
    "            discount = 0\n",
    "        else:\n",
    "            discount = self.promotion.discount(self)\n",
    "        return self.total() - discount\n",
    "    def __repr__(self):\n",
    "        fmt = '<Order total: {:.2f} due: {:.2f}>'\n",
    "        return fmt.format(self.total(), self.due())\n",
    "    \n",
    "class Promotion(ABC): # the Strategy: an Abstract Base Class\n",
    "    @abstractmethod\n",
    "    def discount(self, order):\n",
    "        \"\"\"Return discount as a positive dollar amount\"\"\"\n",
    "        \n",
    "class FidelityPromo(Promotion): # first Concrete Strategy\n",
    "    \"\"\"5% discount for customers with 1000 or more fidelity points\"\"\"\n",
    "    def discount(self, order):\n",
    "        return order.total() * .05 if order.customer.fidelity >= 1000 else 0\n",
    "    \n",
    "class BulkItemPromo(Promotion): # second Concrete Strategy\n",
    "    \"\"\"10% discount for each LineItem with 20 or more units\"\"\"\n",
    "    def discount(self, order):\n",
    "        discount = 0\n",
    "        for item in order.cart:\n",
    "            if item.quantity >= 20:\n",
    "                discount += item.total() * .1\n",
    "        return discount\n",
    "    \n",
    "class LargeOrderPromo(Promotion): # third Concrete Strategy\n",
    "    \"\"\"7% discount for orders with 10 or more distinct items\"\"\"\n",
    "    def discount(self, order):\n",
    "        distinct_items = {item.product for item in order.cart}\n",
    "        if len(distinct_items) >= 10:\n",
    "            return order.total() * .07\n",
    "        return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 42.00>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joe = Customer('John Doe', 200)\n",
    "ann = Customer('Ann Smith', 1100)\n",
    "cart = [LineItem('banana', 4, .5),\n",
    "        LineItem('apple', 10, 1.5),\n",
    "        LineItem('watermellon', 5, 5.0)]\n",
    "Order(joe, cart, FidelityPromo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 39.90>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(ann, cart, FidelityPromo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 30.00 due: 28.50>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "banana_cart = [LineItem('banana', 30, .5),\n",
    "               LineItem('apple', 10, 1.5)]\n",
    "Order(joe, banana_cart, BulkItemPromo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 10.00 due: 9.30>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "long_order = [LineItem(str(item_code), 1, 1.0) for item_code in range(10)]\n",
    "Order(joe, long_order, LargeOrderPromo())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 42.00>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(joe, cart, LargeOrderPromo())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Function-oriented Strategy\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 42.00>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joe = Customer('John Doe', 0)\n",
    "ann = Customer('Ann Smith', 1100)\n",
    "cart = [LineItem('banana', 4, .5),\n",
    "        LineItem('apple', 10, 1.5),\n",
    "        LineItem('watermellon', 5, 5.0)]\n",
    "Order(joe, cart, fidelity_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 39.90>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(ann, cart, fidelity_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 30.00 due: 28.50>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "banana_cart = [LineItem('banana', 30, .5),\n",
    "  LineItem('apple', 10, 1.5)]\n",
    "Order(joe, banana_cart, bulk_item_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 10.00 due: 9.30>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "long_order = [LineItem(str(item_code), 1, 1.0)\n",
    "  for item_code in range(10)]\n",
    "Order(joe, long_order, large_order_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 42.00>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(joe, cart, large_order_promo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choosing the best strategy: simple approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 10.00 due: 9.30>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "promos = [fidelity_promo, bulk_item_promo, large_order_promo]\n",
    "def best_promo(order):\n",
    "    \"\"\"Select best discount available\n",
    "    \"\"\"\n",
    "    return max(promo(order) for promo in promos)\n",
    "\n",
    "Order(joe, long_order, best_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 30.00 due: 28.50>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(joe, banana_cart, best_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 39.90>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Order(ann, cart, best_promo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding strategies in a module\n",
    "Modules in Python are also first class objects, and the Standard Library provides several\n",
    "functions to handle them. The built-in globals is described as follows in the Python\n",
    "docs:\n",
    "globals()\n",
    "Return a dictionary representing the current global symbol table. This is always the\n",
    "dictionary of the current module (inside a function or method, this is the module\n",
    "where it is defined, not the module from which it is called)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 39.90>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "promos = [globals()[name] for name in globals()\n",
    "    if name.endswith('_promo')\n",
    "    and name != 'best_promo']\n",
    "def best_promo(order):\n",
    "    \"\"\"Select best discount available\n",
    "    \"\"\"\n",
    "    return max(promo(order) for promo in promos)\n",
    "Order(ann, cart, best_promo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Order total: 42.00 due: 42.00>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import promotions\n",
    "import inspect\n",
    "promos = [func for name, func in\n",
    "    inspect.getmembers(promotions, inspect.isfunction)]\n",
    "def best_promo(order):\n",
    "    \"\"\"Select best discount available\n",
    "    \"\"\"\n",
    "    return max(promo(order) for promo in promos)\n",
    "\n",
    "joe = Customer('John Doe', 0)\n",
    "ann = Customer('Ann Smith', 1100)\n",
    "cart = [LineItem('banana', 4, .5),\n",
    "        LineItem('apple', 10, 1.5),\n",
    "        LineItem('watermellon', 5, 5.0)]\n",
    "Order(joe, cart, fidelity_promo)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Command\n",
    "![image.png](attachment:image.png)\n",
    "The goal of Command is to decouple an object that invokes an operation (the Invoker)\n",
    "from the provider object that implements it (the Receiver). In the example from the\n",
    "Design Patterns book, each invoker is a menu item in a graphical application, and the\n",
    "receivers are the document being edited or the application itself.\n",
    "\n",
    "The idea is to put a Command object between the two, implementing an interface with\n",
    "a single method, execute, which calls some method in the Receiver to perform the\n",
    "desired operation. That way the Invoker does not need to know the interface of the\n",
    "Receiver, and different receivers can be adapted through different Command subclasses.\n",
    "The Invoker is configured with a concrete command and calls its execute method to\n",
    "operate it.\n",
    "\n",
    "every Python callable implements a single-method interface, and\n",
    "that method is named __call__."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CHAPTER 7 Function decorators and closures\n",
    "## Decorators 101\n",
    "A decorator is a callable that takes another function as argument (the decorated function)\n",
    ". The decorator may perform some processing with the decorated function, and\n",
    "returns it or replaces it with another function or callable object.\n",
    "To summarize: the first crucial fact about decorators is that they have the power to\n",
    "replace the decorated function with a different one. The second crucial fact is that they\n",
    "are executed immediately when a module is loaded.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running inner()\n"
     ]
    }
   ],
   "source": [
    "def deco(func):\n",
    "    def inner():\n",
    "        print('running inner()')\n",
    "    return inner\n",
    "\n",
    "@deco\n",
    "def target():\n",
    "    print('running target()')\n",
    "        \n",
    "target()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function __main__.deco.<locals>.inner>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## When Python executes decorators\n",
    "A key feature of decorators is that they run right after the decorated function is defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running register(<function f1 at 0x0000000005C33EA0>)\n",
      "running register(<function f2 at 0x0000000005C33F28>)\n",
      "running main()\n",
      "registry -> [<function f1 at 0x0000000005C33EA0>, <function f2 at 0x0000000005C33F28>]\n",
      "running f1()\n",
      "running f2()\n",
      "running f3()\n"
     ]
    }
   ],
   "source": [
    "registry = []\n",
    "def register(func):\n",
    "    print('running register(%s)' % func)\n",
    "    registry.append(func)\n",
    "    return func\n",
    "@register\n",
    "def f1():\n",
    "    print('running f1()')\n",
    "@register\n",
    "def f2():\n",
    "    print('running f2()')\n",
    "def f3():\n",
    "    print('running f3()')\n",
    "def main():\n",
    "    print('running main()')\n",
    "    print('registry ->', registry)\n",
    "    f1()\n",
    "    f2()\n",
    "    f3()\n",
    "if __name__=='__main__':\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running register(<function f1 at 0x000000000598F8C8>)\n",
      "running register(<function f2 at 0x000000000598FBF8>)\n"
     ]
    }
   ],
   "source": [
    "import registration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Decorator-enhanced Strategy pattern\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "promos = []\n",
    "def promotion(promo_func):\n",
    "    promos.append(promo_func)\n",
    "    return promo_func\n",
    "@promotion\n",
    "def fidelity(order):\n",
    "    \"\"\"5% discount for customers with 1000 or more fidelity points\"\"\"\n",
    "    return order.total() * .05 if order.customer.fidelity >= 1000 else 0\n",
    "@promotion\n",
    "def bulk_item(order):\n",
    "    \"\"\"10% discount for each LineItem with 20 or more units\"\"\"\n",
    "    discount = 0\n",
    "    for item in order.cart:\n",
    "        if item.quantity >= 20:\n",
    "            discount += item.total() * .1\n",
    "    return discount\n",
    "@promotion\n",
    "def large_order(order):\n",
    "    \"\"\"7% discount for orders with 10 or more distinct items\"\"\"\n",
    "    distinct_items = {item.product for item in order.cart}\n",
    "    if len(distinct_items) >= 10:\n",
    "        return order.total() * .07\n",
    "    return 0\n",
    "def best_promo(order):\n",
    "    \"\"\"Select best discount available\n",
    "    \"\"\"\n",
    "    return max(promo(order) for promo in promos)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Variable scope rules\n",
    "Python does not require you to declare variables,\n",
    "but assumes that a variable assigned in the body of a function is local.\n",
    "\n",
    "If we want the interpreter to treat b as a global variable in spite of the assignment within\n",
    "the function, we use the global declaration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def f1(a):\n",
    "    print(a)\n",
    "    print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'b' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-1dcf6b373e89>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mf1\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-2-06ba9b782704>\u001b[0m in \u001b[0;36mf1\u001b[1;34m(a)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf1\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'b' is not defined"
     ]
    }
   ],
   "source": [
    "f1(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "b=6\n",
    "f1(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def f2(a):\n",
    "    print(a)\n",
    "    print(b)\n",
    "    b = 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n"
     ]
    },
    {
     "ename": "UnboundLocalError",
     "evalue": "local variable 'b' referenced before assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-6-13e7e35f508b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mf2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m8\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-5-70b39fc05ca9>\u001b[0m in \u001b[0;36mf2\u001b[1;34m(a)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mf2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m     \u001b[0mb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m9\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mUnboundLocalError\u001b[0m: local variable 'b' referenced before assignment"
     ]
    }
   ],
   "source": [
    "f2(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "def f3(a):\n",
    "    global b\n",
    "    print(a)\n",
    "    print(b)\n",
    "    b = 9\n",
    "f3(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "f3(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Closures\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class Averager():\n",
    "    def __init__(self):\n",
    "        self.series = []\n",
    "    def __call__(self, new_value):\n",
    "        self.series.append(new_value)\n",
    "        total = sum(self.series)\n",
    "        return total/len(self.series)\n",
    "avg = Averager()\n",
    "avg(10)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.5"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg(13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_averager():\n",
    "    series = []\n",
    "    def averager(new_value):\n",
    "        series.append(new_value)\n",
    "        total = sum(series)\n",
    "        return total/len(series)\n",
    "    return averager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg = make_averager()\n",
    "avg(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.5"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('new_value', 'total')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg.__code__.co_varnames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('series',)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg.__code__.co_freevars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<cell at 0x000000000571FF78: list object at 0x0000000005C4D248>,)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg.__closure__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10, 11, 12]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg.__closure__[0].cell_contents"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To summarize: a closure is function that retains the bindings of the free variables that\n",
    "exist when the function is defined, so that they can be used later when the function is\n",
    "invoked and the defining scope is no longer available.\n",
    "Note that the only situation in which a function may need to deal with external variables\n",
    "that are non-global is when it is nested in another function.\n",
    "## The nonlocal declaration\n",
    "To work around this the nonlocal declaration was introduced in Python 3. It lets you\n",
    "flag a variable as a free variable even when it is assigned a new value within the function.\n",
    "If a new value is assigned to a nonlocal variable, the binding stored in the closure is\n",
    "changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_averager():\n",
    "    count = 0\n",
    "    total = 0\n",
    "    def averager(new_value):\n",
    "        nonlocal count, total\n",
    "        count += 1\n",
    "        total += new_value\n",
    "        return total / count\n",
    "    return averager"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing a simple decorator\n",
    "\n",
    "#### time.perf_counter()\n",
    "Return the value (in fractional seconds) of a performance counter, i.e. a clock with the highest available resolution to measure a short duration. It does include time elapsed during sleep and is system-wide. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Decorators in the standard library\n",
    "### Memoization with functools.lru_cache\n",
    "A very practical decorator is functools.lru_cache. It implements memoization: an\n",
    "optimization technique which works by saving the results of previous invocations of an\n",
    "expensive function, avoiding repeat computations on previously used arguments.\n",
    "Besides making silly recursive algorithms viable, lru_cache really shines in applications\n",
    "that need to fetch information from Web.\n",
    "It’s important to note that lru_cache can be tuned by passing two optional arguments.\n",
    "Its full signature is:\n",
    "functools.lru_cache(maxsize=128, typed=False)\n",
    "\n",
    "The maxsize arguments determines how many call results are stored. After the cache\n",
    "is full, older results are discarded to make room. For optimal performance, maxsize\n",
    "should be a power of 2. The typed argument, if set to True, stores results of different\n",
    "argument types separately, i.e. distinguishing between float and integer arguments that\n",
    "are normally considered equal, like 1 and 1.0. By the way, because lru_cache uses a\n",
    "dict to store the results, and the keys are made from the positional and keyword arguments\n",
    "used in the calls, all the arguments taken by the decorated function must be\n",
    "hashable.\n",
    "### Generic functions with single dispatch\n",
    "The new functools.singledispatch decorator in Python 3.4 allows each module to\n",
    "contribute to the overall solution, and lets you easily provide a specialized function even\n",
    "for classes that you can’t edit. If you decorate a plain function with @singledispatch it\n",
    "becomes a generic function: a group of functions to perform the same operation in\n",
    "different ways, depending on the type of the first argument4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<pre>{1, 2, 3}</pre>'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import html\n",
    "def htmlize(obj):\n",
    "    content = html.escape(repr(obj))\n",
    "    return '<pre>{}</pre>'.format(content)\n",
    "htmlize({1, 2, 3})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<pre>&lt;built-in function abs&gt;</pre>'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "htmlize(abs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<pre>&#x27;Heimlich &amp; Co.\\\\n- a game&#x27;</pre>'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "htmlize('Heimlich & Co.\\n- a game')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<pre>42</pre>'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "htmlize(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pre>[&#x27;alpha&#x27;, 66, {1, 2, 3}]</pre>\n"
     ]
    }
   ],
   "source": [
    "print(htmlize(['alpha', 66, {3, 2, 1}]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from functools import singledispatch\n",
    "from collections import abc\n",
    "import numbers\n",
    "import html\n",
    "@singledispatch\n",
    "def htmlize(obj):\n",
    "    content = html.escape(repr(obj))\n",
    "    return '<pre>{}</pre>'.format(content)\n",
    "@htmlize.register(str)\n",
    "def _(text):\n",
    "    content = html.escape(text).replace('\\n', '<br>\\n')\n",
    "    return '<p>{0}</p>'.format(content)\n",
    "@htmlize.register(numbers.Integral)\n",
    "def _(n):\n",
    "    return '<pre>{0} (0x{0:x})</pre>'.format(n)\n",
    "@htmlize.register(tuple)\n",
    "@htmlize.register(abc.MutableSequence)\n",
    "def _(seq):\n",
    "    inner = '</li>\\n<li>'.join(htmlize(item) for item in seq)\n",
    "    return '<ul>\\n<li>' + inner + '</li>\\n</ul>'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<pre>&lt;built-in function abs&gt;</pre>'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "htmlize(abs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<ul>\n",
      "<li><p>alpha</p></li>\n",
      "<li><pre>66 (0x42)</pre></li>\n",
      "<li><pre>{1, 2, 3}</pre></li>\n",
      "</ul>\n"
     ]
    }
   ],
   "source": [
    "print(htmlize(['alpha', 66, {3, 2, 1}]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### join()函数\n",
    "\n",
    "语法：  'sep'.join(seq)\n",
    "\n",
    "参数说明\n",
    "sep：分隔符。可以为空\n",
    "seq：要连接的元素序列、字符串、元组、字典\n",
    "上面的语法即：以sep作为分隔符，将seq所有的元素合并成一个新的字符串\n",
    "\n",
    "返回值：返回一个以分隔符sep连接各个元素后生成的字符串"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'6</li>\\n<li>9'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " '</li>\\n<li>'.join('69')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stacked decorators\n",
    "\n",
    "When two decorators @d1 and @d2 are applied to a function f in that order, the result is\n",
    "the same as f = d1(d2(f)).\n",
    "\n",
    "## Parametrized Decorators\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running register(<function f1 at 0x0000000006FA1EA0>)\n",
      "running f1()\n",
      "running main()\n",
      "registry -> [<function f1 at 0x0000000006FA1EA0>]\n"
     ]
    }
   ],
   "source": [
    "registry = []\n",
    "def register(func):\n",
    "    print('running register(%s)' % func)\n",
    "    registry.append(func)\n",
    "    return func\n",
    "@register\n",
    "def f1():\n",
    "    print('running f1()')\n",
    "    print('running main()')\n",
    "    print('registry ->', registry)\n",
    "f1()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A parametrized registration decorator\n",
    "### The parametrized clock decorator\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "snooze: 0.12300705909729004s\n",
      "snooze: 0.12300705909729004s\n",
      "snooze: 0.12300705909729004s\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "from clockdeco_param import clock\n",
    "@clock('{name}: {elapsed}s')\n",
    "def snooze(seconds):\n",
    "    time.sleep(seconds)\n",
    "for i in range(3):\n",
    "    snooze(.123)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "snooze(0.123) dt=0.123s\n",
      "snooze(0.123) dt=0.123s\n",
      "snooze(0.123) dt=0.123s\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "from clockdeco_param import clock\n",
    "@clock('{name}({args}) dt={elapsed:0.3f}s')\n",
    "def snooze(seconds):\n",
    "    time.sleep(seconds)\n",
    "for i in range(3):\n",
    "    snooze(.123)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graham Dumpleton and Lennart Regebro — one of this book’s technical\n",
    "reviewers — argue that decorators are best coded as classes implementing\n",
    "__call__, and not as functions like the examples in this\n",
    "chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 函数形参\n",
    "*args 和 **kwargs 主要用于函数定义。你可以将不定数量的参数传递给一个函数。不定的意思是：预先并不知道, 函数使用者会传递多少个参数给你, 所以在这个场景下使用这两个关键字。其实并不是必须写成 *args 和 **kwargs。  *(星号) 才是必须的. 你也可以写成 *ar  和 **k 。而写成 *args 和**kwargs 只是一个通俗的命名约定。\n",
    "python函数传递参数的方式有两种：\n",
    "位置参数（positional argument）\n",
    "关键词参数（keyword argument）\n",
    "*args 与 **kwargs 的区别，两者都是 python 中的可变参数：\n",
    "*args 表示任何多个无名参数，它本质是一个 tuple\n",
    "**kwargs 表示关键字参数，它本质上是一个 dict\n",
    "如果同时使用 *args 和 **kwargs 时，必须 *args 参数列要在 **kwargs 之前。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "args= (1, 2, 3, 4)\n",
      "kwargs= {'A': 'a', 'B': 'b', 'C': 'c', 'D': 'd'}\n"
     ]
    }
   ],
   "source": [
    "def fun(*args, **kwargs):\n",
    "    print('args=', args)\n",
    "    print('kwargs=', kwargs)\n",
    "fun(1, 2, 3, 4, A='a', B='b', C='c', D='d')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### locals()\n",
    "Update and return a dictionary representing the current local symbol table. Free variables are returned by locals() when it is called in function blocks, but not in class blocks.\n",
    "\n",
    "Note The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
